Content related to What Team Do You Need for Successful Knowledge Graph Development?
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterprise and Domain-Specific Semantic Data Sets
Previously at KMWorld 2021, EK joined JPL to share the vision, approach, and delivery of the Institutional Knowledge Graph (IKG), a centrally maintained, ever-evolving knowledge graph identifying and describing JPL’s enterprise-wide concepts, such as people, organizations, projects, and facilities, and … Continue reading
Elevating Your Point Solution to an Enterprise Knowledge Graph
I am fortunate to be able to speak with many vendors in the Graph space, as well as company executives and leaders in IT and KM departments around the world. So many of these people are excited about the power … Continue reading
Jumpstarting Your Semantic Solution Design with UML Diagrams
Where do I start? Whether it be a taxonomy, an ontology, or a knowledge graph, this is a common question that we get from clients when they are beginning their scoping journey. We get it. It is difficult to define … Continue reading
Why Your Data Fabric Needs an Enterprise Ontology
In today’s rapidly growing and evolving data environment, it is increasingly difficult for organizations to get maximal value from the full breadth of their data. As more data is produced faster by more sources, it is difficult for analysts, data … Continue reading
Learning 360: Crafting a Comprehensive View of Learning Content Using a Graph
Chris Marino, a Principal Solution Consultant at Enterprise Knowledge (EK), was a featured speaker at this year’s Data Architecture Online event organized by Dataversity. Marino presented his webinar “Learning 360: Crafting a Comprehensive View of Learning Content Using a Graph” … Continue reading
Expert Analysis: When should my organization use auto-tagging? Part One
As EK works with our clients to design data models, including taxonomies and knowledge graphs, we often implement corresponding auto-tagging solutions to augment the organization and enrichment of unstructured content. In this blog series, two of our senior technical consultants, … Continue reading
The Value of Data Catalogs for Data Scientists
Introduction After the Harvard Business Review called Data Scientist the sexiest job of the 21st century in 2012, much attention went into the interdisciplinary field of data science. Students and professionals were curious to know more about what data scientists … Continue reading
Why Invest in a Knowledge Graph? Your Digital Transformation and Enterprise AI Initiatives Depend on It
The scope and success for digital transformations and advanced enterprise solutions is driven by a few factors, namely, defined use cases, available data, and people and SMEs. For many organizations, the biggest hurdle is knowing where to start. Starting with … Continue reading
Better Practices for Collaborative Knowledge Graph Modeling
As the scale and scope of the modern data ecosystem grows, we at EK see an increasing number of enterprises recognizing the potential for ontologies to make their data findable and usable throughout the organization. An ontology can provide robust … Continue reading
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid Knowledge Graph Implementation
Sara Nash and Thomas Mitrevski, Consultants in Enterprise Knowedge’s Data and Information Management Division presented on May 4, 2022 at the Knowledge Graph Conference in New York City. The talk focused on How to Quickly Prototype a Scalable Graph Architecture: … Continue reading